From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics

Abstract Cancer is a complex disease where cancer cells express epigenetic and transcriptomic mechanisms to promote tumor initiation, progression, and survival. To extract relevant features from the 2019 Cancer Cell Line Encyclopedia (CCLE), a multi-layer nonnegative matrix factorization approach is...

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Autores principales:	T. J. M. Kuijpers, J. C. S. Kleinjans, D. G. J. Jennen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f77ae54171204d649e417f2c0fbed7de
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spelling	oai:doaj.org-article:f77ae54171204d649e417f2c0fbed7de2021-12-02T16:51:14ZFrom multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics10.1038/s41598-021-90047-32045-2322https://doaj.org/article/f77ae54171204d649e417f2c0fbed7de2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-90047-3https://doaj.org/toc/2045-2322Abstract Cancer is a complex disease where cancer cells express epigenetic and transcriptomic mechanisms to promote tumor initiation, progression, and survival. To extract relevant features from the 2019 Cancer Cell Line Encyclopedia (CCLE), a multi-layer nonnegative matrix factorization approach is used. We used relevant feature genes and DNA promoter regions to construct genomic interaction network to study gene–gene and gene—DNA promoter methylation relationships. Here, we identified a set of gene transcripts and methylated DNA promoter regions for different clusters, including one homogeneous lymphoid neoplasms cluster. In this cluster, we found different methylated transcription factors that affect transcriptional activation of EGFR and downstream interactions. Furthermore, the hippo-signaling pathway might not function properly because of DNA hypermethylation and low gene expression of both LATS2 and YAP1. Finally, we could identify a potential dysregulation of the CD28-CD86-CTLA4 axis. Characterizing the interaction of the epigenome and the transcriptome is vital for our understanding of cancer cell line behavior, not only for deepening insights into cancer-related processes but also for future disease treatment and drug development. Here we have identified potential candidates that characterize cancer cell lines, which give insight into the development and progression of cancers.T. J. M. KuijpersJ. C. S. KleinjansD. G. J. JennenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q T. J. M. Kuijpers J. C. S. Kleinjans D. G. J. Jennen From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics
description	Abstract Cancer is a complex disease where cancer cells express epigenetic and transcriptomic mechanisms to promote tumor initiation, progression, and survival. To extract relevant features from the 2019 Cancer Cell Line Encyclopedia (CCLE), a multi-layer nonnegative matrix factorization approach is used. We used relevant feature genes and DNA promoter regions to construct genomic interaction network to study gene–gene and gene—DNA promoter methylation relationships. Here, we identified a set of gene transcripts and methylated DNA promoter regions for different clusters, including one homogeneous lymphoid neoplasms cluster. In this cluster, we found different methylated transcription factors that affect transcriptional activation of EGFR and downstream interactions. Furthermore, the hippo-signaling pathway might not function properly because of DNA hypermethylation and low gene expression of both LATS2 and YAP1. Finally, we could identify a potential dysregulation of the CD28-CD86-CTLA4 axis. Characterizing the interaction of the epigenome and the transcriptome is vital for our understanding of cancer cell line behavior, not only for deepening insights into cancer-related processes but also for future disease treatment and drug development. Here we have identified potential candidates that characterize cancer cell lines, which give insight into the development and progression of cancers.
format	article
author	T. J. M. Kuijpers J. C. S. Kleinjans D. G. J. Jennen
author_facet	T. J. M. Kuijpers J. C. S. Kleinjans D. G. J. Jennen
author_sort	T. J. M. Kuijpers
title	From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics
title_short	From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics
title_full	From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics
title_fullStr	From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics
title_full_unstemmed	From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics
title_sort	from multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/f77ae54171204d649e417f2c0fbed7de
work_keys_str_mv	AT tjmkuijpers frommultiomicsintegrationtowardsnovelgenomicinteractionnetworkstoidentifykeycancercelllinecharacteristics AT jcskleinjans frommultiomicsintegrationtowardsnovelgenomicinteractionnetworkstoidentifykeycancercelllinecharacteristics AT dgjjennen frommultiomicsintegrationtowardsnovelgenomicinteractionnetworkstoidentifykeycancercelllinecharacteristics
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From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics

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